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<a href="_abstract_kernel_function_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a id="l00001" name="l00001"></a><span class="lineno">    1</span><span class="comment">//===========================================================================</span><span class="comment"></span></div>
<div class="line"><a id="l00002" name="l00002"></a><span class="lineno">    2</span><span class="comment">/*!</span></div>
<div class="line"><a id="l00003" name="l00003"></a><span class="lineno">    3</span><span class="comment"> * </span></div>
<div class="line"><a id="l00004" name="l00004"></a><span class="lineno">    4</span><span class="comment"> *</span></div>
<div class="line"><a id="l00005" name="l00005"></a><span class="lineno">    5</span><span class="comment"> * \brief       abstract super class of all kernel functions</span></div>
<div class="line"><a id="l00006" name="l00006"></a><span class="lineno">    6</span><span class="comment"> * \file</span></div>
<div class="line"><a id="l00007" name="l00007"></a><span class="lineno">    7</span><span class="comment"> * </span></div>
<div class="line"><a id="l00008" name="l00008"></a><span class="lineno">    8</span><span class="comment"> *</span></div>
<div class="line"><a id="l00009" name="l00009"></a><span class="lineno">    9</span><span class="comment"> * \author      T.Glasmachers, O. Krause, M. Tuma</span></div>
<div class="line"><a id="l00010" name="l00010"></a><span class="lineno">   10</span><span class="comment"> * \date        2010-2012</span></div>
<div class="line"><a id="l00011" name="l00011"></a><span class="lineno">   11</span><span class="comment"> *</span></div>
<div class="line"><a id="l00012" name="l00012"></a><span class="lineno">   12</span><span class="comment"> *</span></div>
<div class="line"><a id="l00013" name="l00013"></a><span class="lineno">   13</span><span class="comment"> * \par Copyright 1995-2017 Shark Development Team</span></div>
<div class="line"><a id="l00014" name="l00014"></a><span class="lineno">   14</span><span class="comment"> * </span></div>
<div class="line"><a id="l00015" name="l00015"></a><span class="lineno">   15</span><span class="comment"> * &lt;BR&gt;&lt;HR&gt;</span></div>
<div class="line"><a id="l00016" name="l00016"></a><span class="lineno">   16</span><span class="comment"> * This file is part of Shark.</span></div>
<div class="line"><a id="l00017" name="l00017"></a><span class="lineno">   17</span><span class="comment"> * &lt;https://shark-ml.github.io/Shark/&gt;</span></div>
<div class="line"><a id="l00018" name="l00018"></a><span class="lineno">   18</span><span class="comment"> * </span></div>
<div class="line"><a id="l00019" name="l00019"></a><span class="lineno">   19</span><span class="comment"> * Shark is free software: you can redistribute it and/or modify</span></div>
<div class="line"><a id="l00020" name="l00020"></a><span class="lineno">   20</span><span class="comment"> * it under the terms of the GNU Lesser General Public License as published </span></div>
<div class="line"><a id="l00021" name="l00021"></a><span class="lineno">   21</span><span class="comment"> * by the Free Software Foundation, either version 3 of the License, or</span></div>
<div class="line"><a id="l00022" name="l00022"></a><span class="lineno">   22</span><span class="comment"> * (at your option) any later version.</span></div>
<div class="line"><a id="l00023" name="l00023"></a><span class="lineno">   23</span><span class="comment"> * </span></div>
<div class="line"><a id="l00024" name="l00024"></a><span class="lineno">   24</span><span class="comment"> * Shark is distributed in the hope that it will be useful,</span></div>
<div class="line"><a id="l00025" name="l00025"></a><span class="lineno">   25</span><span class="comment"> * but WITHOUT ANY WARRANTY; without even the implied warranty of</span></div>
<div class="line"><a id="l00026" name="l00026"></a><span class="lineno">   26</span><span class="comment"> * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the</span></div>
<div class="line"><a id="l00027" name="l00027"></a><span class="lineno">   27</span><span class="comment"> * GNU Lesser General Public License for more details.</span></div>
<div class="line"><a id="l00028" name="l00028"></a><span class="lineno">   28</span><span class="comment"> * </span></div>
<div class="line"><a id="l00029" name="l00029"></a><span class="lineno">   29</span><span class="comment"> * You should have received a copy of the GNU Lesser General Public License</span></div>
<div class="line"><a id="l00030" name="l00030"></a><span class="lineno">   30</span><span class="comment"> * along with Shark.  If not, see &lt;http://www.gnu.org/licenses/&gt;.</span></div>
<div class="line"><a id="l00031" name="l00031"></a><span class="lineno">   31</span><span class="comment"> *</span></div>
<div class="line"><a id="l00032" name="l00032"></a><span class="lineno">   32</span><span class="comment"> */</span></div>
<div class="line"><a id="l00033" name="l00033"></a><span class="lineno">   33</span><span class="comment">//===========================================================================</span></div>
<div class="line"><a id="l00034" name="l00034"></a><span class="lineno">   34</span> </div>
<div class="line"><a id="l00035" name="l00035"></a><span class="lineno">   35</span><span class="preprocessor">#ifndef SHARK_MODELS_KERNELS_ABSTRACTKERNELFUNCTION_H</span></div>
<div class="line"><a id="l00036" name="l00036"></a><span class="lineno">   36</span><span class="preprocessor">#define SHARK_MODELS_KERNELS_ABSTRACTKERNELFUNCTION_H</span></div>
<div class="line"><a id="l00037" name="l00037"></a><span class="lineno">   37</span> </div>
<div class="line"><a id="l00038" name="l00038"></a><span class="lineno">   38</span><span class="preprocessor">#include &lt;<a class="code" href="_abstract_metric_8h.html">shark/Models/Kernels/AbstractMetric.h</a>&gt;</span></div>
<div class="line"><a id="l00039" name="l00039"></a><span class="lineno">   39</span><span class="preprocessor">#include &lt;<a class="code" href="_base_8h.html">shark/LinAlg/Base.h</a>&gt;</span></div>
<div class="line"><a id="l00040" name="l00040"></a><span class="lineno">   40</span><span class="preprocessor">#include &lt;<a class="code" href="_flags_8h.html">shark/Core/Flags.h</a>&gt;</span></div>
<div class="line"><a id="l00041" name="l00041"></a><span class="lineno">   41</span><span class="preprocessor">#include &lt;<a class="code" href="_state_8h.html">shark/Core/State.h</a>&gt;</span></div>
<div class="line"><a id="l00042" name="l00042"></a><span class="lineno">   42</span><span class="keyword">namespace </span><a class="code hl_namespace" href="namespaceshark.html" title="AbstractMultiObjectiveOptimizer.">shark</a> {</div>
<div class="line"><a id="l00043" name="l00043"></a><span class="lineno">   43</span> </div>
<div class="line"><a id="l00044" name="l00044"></a><span class="lineno">   44</span><span class="preprocessor">#ifdef SHARK_COUNT_KERNEL_LOOKUPS</span></div>
<div class="line"><a id="l00045" name="l00045"></a><span class="lineno">   45</span><span class="preprocessor">    #define INCREMENT_KERNEL_COUNTER( counter ) { counter++; }</span></div>
<div class="line"><a id="l00046" name="l00046"></a><span class="lineno">   46</span><span class="preprocessor">#else</span></div>
<div class="line"><a id="l00047" name="l00047"></a><span class="lineno"><a class="line" href="_abstract_kernel_function_8h.html#a6b3350b06ce58818fa3509b6ec779aef">   47</a></span><span class="preprocessor">    #define INCREMENT_KERNEL_COUNTER( counter ) {  }</span></div>
<div class="line"><a id="l00048" name="l00048"></a><span class="lineno">   48</span><span class="preprocessor">#endif</span></div>
<div class="line"><a id="l00049" name="l00049"></a><span class="lineno">   49</span>    <span class="comment"></span></div>
<div class="line"><a id="l00050" name="l00050"></a><span class="lineno">   50</span><span class="comment">///\defgroup kernels Kernels</span></div>
<div class="line"><a id="l00051" name="l00051"></a><span class="lineno">   51</span><span class="comment">///\ingroup models</span></div>
<div class="line"><a id="l00052" name="l00052"></a><span class="lineno">   52</span><span class="comment">///</span></div>
<div class="line"><a id="l00053" name="l00053"></a><span class="lineno">   53</span><span class="comment">/// A kernel is a positive definite function k(x,y), which can be understood as a generalized scalar product. Kernel methods.</span></div>
<div class="line"><a id="l00054" name="l00054"></a><span class="lineno">   54</span><span class="comment">/// like support vector machines or gaussian processes rely on the kernels.</span></div>
<div class="line"><a id="l00055" name="l00055"></a><span class="lineno">   55</span><span class="comment"></span><span class="comment"></span> </div>
<div class="line"><a id="l00056" name="l00056"></a><span class="lineno">   56</span><span class="comment">/// \brief Base class of all Kernel functions.</span></div>
<div class="line"><a id="l00057" name="l00057"></a><span class="lineno">   57</span><span class="comment">///</span></div>
<div class="line"><a id="l00058" name="l00058"></a><span class="lineno">   58</span><span class="comment">/// \par</span></div>
<div class="line"><a id="l00059" name="l00059"></a><span class="lineno">   59</span><span class="comment">/// A (Mercer) kernel is a symmetric positive definite</span></div>
<div class="line"><a id="l00060" name="l00060"></a><span class="lineno">   60</span><span class="comment">/// function of two parameters. It is (currently) used</span></div>
<div class="line"><a id="l00061" name="l00061"></a><span class="lineno">   61</span><span class="comment">/// in two contexts in Shark, namely for kernel methods</span></div>
<div class="line"><a id="l00062" name="l00062"></a><span class="lineno">   62</span><span class="comment">/// such as support vector machines (SVMs), and for</span></div>
<div class="line"><a id="l00063" name="l00063"></a><span class="lineno">   63</span><span class="comment">/// radial basis function networks.</span></div>
<div class="line"><a id="l00064" name="l00064"></a><span class="lineno">   64</span><span class="comment">///</span></div>
<div class="line"><a id="l00065" name="l00065"></a><span class="lineno">   65</span><span class="comment">/// \par</span></div>
<div class="line"><a id="l00066" name="l00066"></a><span class="lineno">   66</span><span class="comment">/// In Shark a kernel function class represents a parametric</span></div>
<div class="line"><a id="l00067" name="l00067"></a><span class="lineno">   67</span><span class="comment">/// family of such kernel functions: The AbstractKernelFunction</span></div>
<div class="line"><a id="l00068" name="l00068"></a><span class="lineno">   68</span><span class="comment">/// interface inherits the IParameterizable interface.</span></div>
<div class="line"><a id="l00069" name="l00069"></a><span class="lineno">   69</span><span class="comment">/// \ingroup kernels</span></div>
<div class="line"><a id="l00070" name="l00070"></a><span class="lineno">   70</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> InputTypeT&gt;</div>
<div class="foldopen" id="foldopen00071" data-start="{" data-end="};">
<div class="line"><a id="l00071" name="l00071"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html">   71</a></span><span class="keyword">class </span><a class="code hl_class" href="classshark_1_1_abstract_kernel_function.html" title="Base class of all Kernel functions.">AbstractKernelFunction</a> : <span class="keyword">public</span> <a class="code hl_class" href="classshark_1_1_abstract_metric.html" title="Base-class for metrics.">AbstractMetric</a>&lt;InputTypeT&gt;</div>
<div class="line"><a id="l00072" name="l00072"></a><span class="lineno">   72</span>{</div>
<div class="line"><a id="l00073" name="l00073"></a><span class="lineno">   73</span><span class="keyword">private</span>:</div>
<div class="line"><a id="l00074" name="l00074"></a><span class="lineno">   74</span>    <span class="keyword">typedef</span> <a class="code hl_class" href="classshark_1_1_abstract_metric.html" title="Base-class for metrics.">AbstractMetric&lt;InputTypeT&gt;</a> <a class="code hl_class" href="classshark_1_1_abstract_metric.html" title="Base-class for metrics.">base_type</a>;</div>
<div class="line"><a id="l00075" name="l00075"></a><span class="lineno">   75</span>    <span class="keyword">typedef</span> <a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">Batch&lt;InputTypeT&gt;</a> <a class="code hl_struct" href="structshark_1_1_batch.html" title="class which helps using different batch types">Traits</a>;</div>
<div class="line"><a id="l00076" name="l00076"></a><span class="lineno">   76</span><span class="keyword">public</span>:<span class="comment"></span></div>
<div class="line"><a id="l00077" name="l00077"></a><span class="lineno">   77</span><span class="comment">    /// \brief  Input type of the Kernel.</span></div>
<div class="line"><a id="l00078" name="l00078"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#a808acb34b9c95c6af0f48177d554bd59">   78</a></span><span class="comment"></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code hl_typedef" href="classshark_1_1_abstract_metric.html#a8ef376e183e0fac88fc9234204c75569" title="Input type of the Kernel.">base_type::InputType</a> <a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#a808acb34b9c95c6af0f48177d554bd59" title="Input type of the Kernel.">InputType</a>;<span class="comment"></span></div>
<div class="line"><a id="l00079" name="l00079"></a><span class="lineno">   79</span><span class="comment">    /// \brief batch input type of the kernel</span></div>
<div class="line"><a id="l00080" name="l00080"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#adbf700c2ece7236c70cef4b88777a733">   80</a></span><span class="comment"></span>    <span class="keyword">typedef</span>  <span class="keyword">typename</span> <a class="code hl_typedef" href="classshark_1_1_abstract_metric.html#a3ed2427fcee73de8368e0e24ce61cada" title="batch input type of the kernel">base_type::BatchInputType</a> <a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#adbf700c2ece7236c70cef4b88777a733" title="batch input type of the kernel">BatchInputType</a>;<span class="comment"></span></div>
<div class="line"><a id="l00081" name="l00081"></a><span class="lineno">   81</span><span class="comment">    /// \brief Const references to InputType</span></div>
<div class="line"><a id="l00082" name="l00082"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#a40e365cb5ec7d2776105a4aef4e78df3">   82</a></span><span class="comment"></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code hl_typedef" href="classshark_1_1_abstract_metric.html#ad56b88ee5dab414cc3fe71ef6a36aa19" title="Const references to InputType.">base_type::ConstInputReference</a> <a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#a40e365cb5ec7d2776105a4aef4e78df3" title="Const references to InputType.">ConstInputReference</a>;<span class="comment"></span></div>
<div class="line"><a id="l00083" name="l00083"></a><span class="lineno">   83</span><span class="comment">    /// \brief Const references to BatchInputType</span></div>
<div class="line"><a id="l00084" name="l00084"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#af923f26f3d015156bb5ac159b302311b">   84</a></span><span class="comment"></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code hl_typedef" href="classshark_1_1_abstract_metric.html#aded3435936965bcee46366318e37cbc9" title="Const references to BatchInputType.">base_type::ConstBatchInputReference</a> <a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#af923f26f3d015156bb5ac159b302311b" title="Const references to BatchInputType.">ConstBatchInputReference</a>;</div>
<div class="line"><a id="l00085" name="l00085"></a><span class="lineno">   85</span> </div>
<div class="line"><a id="l00086" name="l00086"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#a81ed7e2e580d7967ba21d82cf8105c4c">   86</a></span>    <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#a81ed7e2e580d7967ba21d82cf8105c4c">AbstractKernelFunction</a>() { }</div>
<div class="line"><a id="l00087" name="l00087"></a><span class="lineno">   87</span>    <span class="comment"></span></div>
<div class="line"><a id="l00088" name="l00088"></a><span class="lineno">   88</span><span class="comment">    /// enumerations of kerneland metric features (flags)</span></div>
<div class="foldopen" id="foldopen00089" data-start="{" data-end="};">
<div class="line"><a id="l00089" name="l00089"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#af54c80ca837961761506e6c2eec15bde">   89</a></span><span class="comment"></span>    <span class="keyword">enum</span> <a class="code hl_enumeration" href="classshark_1_1_abstract_kernel_function.html#af54c80ca837961761506e6c2eec15bde" title="enumerations of kerneland metric features (flags)">Feature</a> {</div>
<div class="line"><a id="l00090" name="l00090"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#af54c80ca837961761506e6c2eec15bdead621a9ae065d91a154055a38a7ea72f8">   90</a></span>        <a class="code hl_enumvalue" href="classshark_1_1_abstract_kernel_function.html#af54c80ca837961761506e6c2eec15bdead621a9ae065d91a154055a38a7ea72f8" title="is the kernel differentiable w.r.t. its parameters?">HAS_FIRST_PARAMETER_DERIVATIVE</a> = 1,    <span class="comment">///&lt; is the kernel differentiable w.r.t. its parameters?</span></div>
<div class="line"><a id="l00091" name="l00091"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#af54c80ca837961761506e6c2eec15bdeae4bd575af084f862f64bc665cad4c4ec">   91</a></span>        <a class="code hl_enumvalue" href="classshark_1_1_abstract_kernel_function.html#af54c80ca837961761506e6c2eec15bdeae4bd575af084f862f64bc665cad4c4ec" title="is the kernel differentiable w.r.t. its inputs?">HAS_FIRST_INPUT_DERIVATIVE</a>     = 2,    <span class="comment">///&lt; is the kernel differentiable w.r.t. its inputs?</span></div>
<div class="line"><a id="l00092" name="l00092"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#af54c80ca837961761506e6c2eec15bdea389ad713fc9ba77daf7a89714e5db666">   92</a></span>        <a class="code hl_enumvalue" href="classshark_1_1_abstract_kernel_function.html#af54c80ca837961761506e6c2eec15bdea389ad713fc9ba77daf7a89714e5db666" title="does k(x, x) = 1 hold for all inputs x?">IS_NORMALIZED</a>                  = 4 ,   <span class="comment">///&lt; does k(x, x) = 1 hold for all inputs x?</span></div>
<div class="line"><a id="l00093" name="l00093"></a><span class="lineno">   93</span>        <a class="code hl_enumvalue" href="classshark_1_1_abstract_kernel_function.html#af54c80ca837961761506e6c2eec15bdeae04fd78a7baf17b1591cdb6ef289e8d1" title="Input arguments must have same size, but not the same size in different calls to eval.">SUPPORTS_VARIABLE_INPUT_SIZE</a> = 8 <span class="comment">///&lt; Input arguments must have same size, but not the same size in different calls to eval</span></div>
<div class="line"><a id="l00094" name="l00094"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#af54c80ca837961761506e6c2eec15bdeae04fd78a7baf17b1591cdb6ef289e8d1">   94</a></span>    };</div>
</div>
<div class="line"><a id="l00095" name="l00095"></a><span class="lineno">   95</span>    <span class="comment"></span></div>
<div class="line"><a id="l00096" name="l00096"></a><span class="lineno">   96</span><span class="comment">    /// This statement declares the member m_features. See Core/Flags.h for details.</span></div>
<div class="line"><a id="l00097" name="l00097"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#a619eef1551440a251e305cc6cd88d2f8">   97</a></span><span class="comment"></span>    <a class="code hl_define" href="_flags_8h.html#a3c3e2d17f85cf4a10ea888742a4b95a3">SHARK_FEATURE_INTERFACE</a>;</div>
<div class="line"><a id="l00098" name="l00098"></a><span class="lineno">   98</span>    </div>
<div class="foldopen" id="foldopen00099" data-start="{" data-end="}">
<div class="line"><a id="l00099" name="l00099"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#ac0c799ac75db64200256ed50d34d2411">   99</a></span>    <span class="keywordtype">bool</span> <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#ac0c799ac75db64200256ed50d34d2411">hasFirstParameterDerivative</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00100" name="l00100"></a><span class="lineno">  100</span>        <span class="keywordflow">return</span> <a class="code hl_variable" href="classshark_1_1_abstract_kernel_function.html#aa13e9ab3b8bbad9e1d773468671703e6">m_features</a> &amp; <a class="code hl_enumvalue" href="classshark_1_1_abstract_kernel_function.html#af54c80ca837961761506e6c2eec15bdead621a9ae065d91a154055a38a7ea72f8" title="is the kernel differentiable w.r.t. its parameters?">HAS_FIRST_PARAMETER_DERIVATIVE</a>;</div>
<div class="line"><a id="l00101" name="l00101"></a><span class="lineno">  101</span>    }</div>
</div>
<div class="foldopen" id="foldopen00102" data-start="{" data-end="}">
<div class="line"><a id="l00102" name="l00102"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#a505ca00275044073f08aae949127a76f">  102</a></span>    <span class="keywordtype">bool</span> <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#a505ca00275044073f08aae949127a76f">hasFirstInputDerivative</a>()<span class="keyword">const</span>{</div>
<div class="line"><a id="l00103" name="l00103"></a><span class="lineno">  103</span>        <span class="keywordflow">return</span> <a class="code hl_variable" href="classshark_1_1_abstract_kernel_function.html#aa13e9ab3b8bbad9e1d773468671703e6">m_features</a> &amp; <a class="code hl_enumvalue" href="classshark_1_1_abstract_kernel_function.html#af54c80ca837961761506e6c2eec15bdeae4bd575af084f862f64bc665cad4c4ec" title="is the kernel differentiable w.r.t. its inputs?">HAS_FIRST_INPUT_DERIVATIVE</a>;</div>
<div class="line"><a id="l00104" name="l00104"></a><span class="lineno">  104</span>    }</div>
</div>
<div class="foldopen" id="foldopen00105" data-start="{" data-end="}">
<div class="line"><a id="l00105" name="l00105"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#a3b60def6354aac30a9c2ce5bffa6f9ae">  105</a></span>    <span class="keywordtype">bool</span> <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#a3b60def6354aac30a9c2ce5bffa6f9ae">isNormalized</a>()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00106" name="l00106"></a><span class="lineno">  106</span>        <span class="keywordflow">return</span> <a class="code hl_variable" href="classshark_1_1_abstract_kernel_function.html#aa13e9ab3b8bbad9e1d773468671703e6">m_features</a> &amp; <a class="code hl_enumvalue" href="classshark_1_1_abstract_kernel_function.html#af54c80ca837961761506e6c2eec15bdea389ad713fc9ba77daf7a89714e5db666" title="does k(x, x) = 1 hold for all inputs x?">IS_NORMALIZED</a>;</div>
<div class="line"><a id="l00107" name="l00107"></a><span class="lineno">  107</span>    }</div>
</div>
<div class="foldopen" id="foldopen00108" data-start="{" data-end="}">
<div class="line"><a id="l00108" name="l00108"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#a225fbad3a0efdac21e4422576de2ce4e">  108</a></span>    <span class="keywordtype">bool</span> <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#a225fbad3a0efdac21e4422576de2ce4e">supportsVariableInputSize</a>()<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00109" name="l00109"></a><span class="lineno">  109</span>        <span class="keywordflow">return</span> <a class="code hl_variable" href="classshark_1_1_abstract_kernel_function.html#aa13e9ab3b8bbad9e1d773468671703e6">m_features</a> &amp; <a class="code hl_enumvalue" href="classshark_1_1_abstract_kernel_function.html#af54c80ca837961761506e6c2eec15bdeae04fd78a7baf17b1591cdb6ef289e8d1" title="Input arguments must have same size, but not the same size in different calls to eval.">SUPPORTS_VARIABLE_INPUT_SIZE</a>;</div>
<div class="line"><a id="l00110" name="l00110"></a><span class="lineno">  110</span>    }</div>
</div>
<div class="line"><a id="l00111" name="l00111"></a><span class="lineno">  111</span><span class="comment"></span> </div>
<div class="line"><a id="l00112" name="l00112"></a><span class="lineno">  112</span><span class="comment">    ///\brief Creates an internal state of the kernel.</span></div>
<div class="line"><a id="l00113" name="l00113"></a><span class="lineno">  113</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00114" name="l00114"></a><span class="lineno">  114</span><span class="comment">    ///The state is needed when the derivatives are to be</span></div>
<div class="line"><a id="l00115" name="l00115"></a><span class="lineno">  115</span><span class="comment">    ///calculated. Eval can store a state which is then reused to speed up</span></div>
<div class="line"><a id="l00116" name="l00116"></a><span class="lineno">  116</span><span class="comment">    ///the calculations of the derivatives. This also allows eval to be</span></div>
<div class="line"><a id="l00117" name="l00117"></a><span class="lineno">  117</span><span class="comment">    ///evaluated in parallel!</span></div>
<div class="foldopen" id="foldopen00118" data-start="{" data-end="}">
<div class="line"><a id="l00118" name="l00118"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#a9057a4a71b4d28febb171e09bbd22c07">  118</a></span><span class="comment"></span>    <span class="keyword">virtual</span> boost::shared_ptr&lt;State&gt; <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#a9057a4a71b4d28febb171e09bbd22c07" title="Creates an internal state of the kernel.">createState</a>()<span class="keyword">const</span></div>
<div class="line"><a id="l00119" name="l00119"></a><span class="lineno">  119</span><span class="keyword">    </span>{</div>
<div class="line"><a id="l00120" name="l00120"></a><span class="lineno">  120</span>        <a class="code hl_define" href="_exception_8h.html#adce1f80097c69010f5eab2618fa2e971">SHARK_RUNTIME_CHECK</a>(!<a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#ac0c799ac75db64200256ed50d34d2411">hasFirstParameterDerivative</a>() &amp;&amp; !<a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#a505ca00275044073f08aae949127a76f">hasFirstInputDerivative</a>(), <span class="stringliteral">&quot;createState must be overridden by kernels with derivatives&quot;</span>);</div>
<div class="line"><a id="l00121" name="l00121"></a><span class="lineno">  121</span>        <span class="keywordflow">return</span> boost::shared_ptr&lt;State&gt;(<span class="keyword">new</span> <a class="code hl_struct" href="structshark_1_1_empty_state.html" title="Default State of an Object which does not need a State.">EmptyState</a>());</div>
<div class="line"><a id="l00122" name="l00122"></a><span class="lineno">  122</span>    }</div>
</div>
<div class="line"><a id="l00123" name="l00123"></a><span class="lineno">  123</span><span class="comment"></span> </div>
<div class="line"><a id="l00124" name="l00124"></a><span class="lineno">  124</span><span class="comment">    ///////////////////////////////////////////SINGLE ELEMENT INTERFACE///////////////////////////////////////////</span></div>
<div class="line"><a id="l00125" name="l00125"></a><span class="lineno">  125</span><span class="comment"></span>    <span class="comment">// By default, this is mapped to the batch case.</span></div>
<div class="line"><a id="l00126" name="l00126"></a><span class="lineno">  126</span><span class="comment"></span> </div>
<div class="line"><a id="l00127" name="l00127"></a><span class="lineno">  127</span><span class="comment">    /// \brief Evaluates the kernel function.</span></div>
<div class="foldopen" id="foldopen00128" data-start="{" data-end="}">
<div class="line"><a id="l00128" name="l00128"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#abd10e3815efade90c7f9e2a7cc8bcb6c">  128</a></span><span class="comment"></span>    <span class="keyword">virtual</span> <span class="keywordtype">double</span> <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#abd10e3815efade90c7f9e2a7cc8bcb6c" title="Evaluates the kernel function.">eval</a>(<a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#a40e365cb5ec7d2776105a4aef4e78df3" title="Const references to InputType.">ConstInputReference</a> x1, <a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#a40e365cb5ec7d2776105a4aef4e78df3" title="Const references to InputType.">ConstInputReference</a> x2)<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00129" name="l00129"></a><span class="lineno">  129</span>        RealMatrix res;</div>
<div class="line"><a id="l00130" name="l00130"></a><span class="lineno">  130</span>        <a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#adbf700c2ece7236c70cef4b88777a733" title="batch input type of the kernel">BatchInputType</a> b1 = Traits::createBatch(x1,1);</div>
<div class="line"><a id="l00131" name="l00131"></a><span class="lineno">  131</span>        <a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#adbf700c2ece7236c70cef4b88777a733" title="batch input type of the kernel">BatchInputType</a> b2 = Traits::createBatch(x2,1);</div>
<div class="line"><a id="l00132" name="l00132"></a><span class="lineno">  132</span>        <a class="code hl_function" href="namespaceshark.html#a1531880b9b4076854b0b26441d353242">getBatchElement</a>(b1,0) = x1;</div>
<div class="line"><a id="l00133" name="l00133"></a><span class="lineno">  133</span>        <a class="code hl_function" href="namespaceshark.html#a1531880b9b4076854b0b26441d353242">getBatchElement</a>(b2,0) = x2;</div>
<div class="line"><a id="l00134" name="l00134"></a><span class="lineno">  134</span>        <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#abd10e3815efade90c7f9e2a7cc8bcb6c" title="Evaluates the kernel function.">eval</a>(b1, b2, res);</div>
<div class="line"><a id="l00135" name="l00135"></a><span class="lineno">  135</span>        <span class="keywordflow">return</span> res(0, 0);</div>
<div class="line"><a id="l00136" name="l00136"></a><span class="lineno">  136</span>    }</div>
</div>
<div class="line"><a id="l00137" name="l00137"></a><span class="lineno">  137</span><span class="comment"></span> </div>
<div class="line"><a id="l00138" name="l00138"></a><span class="lineno">  138</span><span class="comment">    /// \brief Convenience operator which evaluates the kernel function.</span></div>
<div class="foldopen" id="foldopen00139" data-start="{" data-end="}">
<div class="line"><a id="l00139" name="l00139"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#a187783089e5ee24875e43b8865b1a46e">  139</a></span><span class="comment"></span>    <span class="keyword">inline</span> <span class="keywordtype">double</span> <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#a187783089e5ee24875e43b8865b1a46e" title="Convenience operator which evaluates the kernel function.">operator () </a>(<a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#a40e365cb5ec7d2776105a4aef4e78df3" title="Const references to InputType.">ConstInputReference</a> x1, <a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#a40e365cb5ec7d2776105a4aef4e78df3" title="Const references to InputType.">ConstInputReference</a> x2)<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00140" name="l00140"></a><span class="lineno">  140</span>        <span class="keywordflow">return</span> <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#abd10e3815efade90c7f9e2a7cc8bcb6c" title="Evaluates the kernel function.">eval</a>(x1, x2);</div>
<div class="line"><a id="l00141" name="l00141"></a><span class="lineno">  141</span>    }</div>
</div>
<div class="line"><a id="l00142" name="l00142"></a><span class="lineno">  142</span><span class="comment"></span> </div>
<div class="line"><a id="l00143" name="l00143"></a><span class="lineno">  143</span><span class="comment">    //////////////////////////////////////BATCH INTERFACE///////////////////////////////////////////</span></div>
<div class="line"><a id="l00144" name="l00144"></a><span class="lineno">  144</span><span class="comment"></span>    <span class="comment"></span></div>
<div class="line"><a id="l00145" name="l00145"></a><span class="lineno">  145</span><span class="comment">    /// \brief Evaluates the subset of the KernelGram matrix which is defined by X1(rows) and X2 (columns).</span></div>
<div class="line"><a id="l00146" name="l00146"></a><span class="lineno">  146</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00147" name="l00147"></a><span class="lineno">  147</span><span class="comment">    /// The result matrix is filled in with the values result(i,j) = kernel(x1[i], x2[j]);</span></div>
<div class="line"><a id="l00148" name="l00148"></a><span class="lineno">  148</span><span class="comment">    /// The State object is filled in with data used in subsequent derivative computations.</span></div>
<div class="line"><a id="l00149" name="l00149"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#af9edfdfdd3cbee76f67f47cf244f8b3b">  149</a></span><span class="comment"></span>    <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#af9edfdfdd3cbee76f67f47cf244f8b3b" title="Evaluates the subset of the KernelGram matrix which is defined by X1(rows) and X2 (columns).">eval</a>(<a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#af923f26f3d015156bb5ac159b302311b" title="Const references to BatchInputType.">ConstBatchInputReference</a> batchX1, <a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#af923f26f3d015156bb5ac159b302311b" title="Const references to BatchInputType.">ConstBatchInputReference</a> batchX2, RealMatrix&amp; result, <a class="code hl_struct" href="structshark_1_1_state.html" title="Represents the State of an Object.">State</a>&amp; state) <span class="keyword">const</span> = 0;</div>
<div class="line"><a id="l00150" name="l00150"></a><span class="lineno">  150</span><span class="comment"></span> </div>
<div class="line"><a id="l00151" name="l00151"></a><span class="lineno">  151</span><span class="comment">    /// \brief Evaluates the subset of the KernelGram matrix which is defined by X1(rows) and X2 (columns).</span></div>
<div class="line"><a id="l00152" name="l00152"></a><span class="lineno">  152</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00153" name="l00153"></a><span class="lineno">  153</span><span class="comment">    /// The result matrix is filled in with the values result(i,j) = kernel(x1[i], x2[j]);</span></div>
<div class="foldopen" id="foldopen00154" data-start="{" data-end="}">
<div class="line"><a id="l00154" name="l00154"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#abfb9bc53f137dc1e28bf875e8851c26b">  154</a></span><span class="comment"></span>    <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#abfb9bc53f137dc1e28bf875e8851c26b" title="Evaluates the subset of the KernelGram matrix which is defined by X1(rows) and X2 (columns).">eval</a>(<a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#af923f26f3d015156bb5ac159b302311b" title="Const references to BatchInputType.">ConstBatchInputReference</a> batchX1, <a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#af923f26f3d015156bb5ac159b302311b" title="Const references to BatchInputType.">ConstBatchInputReference</a> batchX2, RealMatrix&amp; result)<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00155" name="l00155"></a><span class="lineno">  155</span>        boost::shared_ptr&lt;State&gt; state = <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#a9057a4a71b4d28febb171e09bbd22c07" title="Creates an internal state of the kernel.">createState</a>();</div>
<div class="line"><a id="l00156" name="l00156"></a><span class="lineno">  156</span>        <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#abd10e3815efade90c7f9e2a7cc8bcb6c" title="Evaluates the kernel function.">eval</a>(batchX1, batchX2, result, *state);</div>
<div class="line"><a id="l00157" name="l00157"></a><span class="lineno">  157</span>    }</div>
</div>
<div class="line"><a id="l00158" name="l00158"></a><span class="lineno">  158</span><span class="comment"></span> </div>
<div class="line"><a id="l00159" name="l00159"></a><span class="lineno">  159</span><span class="comment">    /// \brief Evaluates the subset of the KernelGram matrix which is defined by X1(rows) and X2 (columns).</span></div>
<div class="line"><a id="l00160" name="l00160"></a><span class="lineno">  160</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00161" name="l00161"></a><span class="lineno">  161</span><span class="comment">    /// Convenience operator.</span></div>
<div class="line"><a id="l00162" name="l00162"></a><span class="lineno">  162</span><span class="comment">    /// The result matrix is filled in with the values result(i,j) = kernel(x1[i], x2[j]);</span></div>
<div class="foldopen" id="foldopen00163" data-start="{" data-end="}">
<div class="line"><a id="l00163" name="l00163"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#a2d5586ade0c39f0513c8e53ec5f99ed6">  163</a></span><span class="comment"></span>    <span class="keyword">inline</span> RealMatrix <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#a187783089e5ee24875e43b8865b1a46e" title="Convenience operator which evaluates the kernel function.">operator () </a>(<a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#af923f26f3d015156bb5ac159b302311b" title="Const references to BatchInputType.">ConstBatchInputReference</a> batchX1, <a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#af923f26f3d015156bb5ac159b302311b" title="Const references to BatchInputType.">ConstBatchInputReference</a> batchX2)<span class="keyword"> const</span>{ </div>
<div class="line"><a id="l00164" name="l00164"></a><span class="lineno">  164</span>        RealMatrix result;</div>
<div class="line"><a id="l00165" name="l00165"></a><span class="lineno">  165</span>        <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#abd10e3815efade90c7f9e2a7cc8bcb6c" title="Evaluates the kernel function.">eval</a>(batchX1, batchX2, result);</div>
<div class="line"><a id="l00166" name="l00166"></a><span class="lineno">  166</span>        <span class="keywordflow">return</span> result;</div>
<div class="line"><a id="l00167" name="l00167"></a><span class="lineno">  167</span>    }</div>
</div>
<div class="line"><a id="l00168" name="l00168"></a><span class="lineno">  168</span><span class="comment"></span> </div>
<div class="line"><a id="l00169" name="l00169"></a><span class="lineno">  169</span><span class="comment">    /// \brief Computes the gradient of the parameters as a weighted sum over the gradient of all elements of the batch.</span></div>
<div class="line"><a id="l00170" name="l00170"></a><span class="lineno">  170</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00171" name="l00171"></a><span class="lineno">  171</span><span class="comment">    /// The default implementation throws a &quot;not implemented&quot; exception.</span></div>
<div class="foldopen" id="foldopen00172" data-start="{" data-end="}">
<div class="line"><a id="l00172" name="l00172"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#a48557b9834bc06ccb4e005ce441904c8">  172</a></span><span class="comment"></span>    <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#a48557b9834bc06ccb4e005ce441904c8" title="Computes the gradient of the parameters as a weighted sum over the gradient of all elements of the ba...">weightedParameterDerivative</a>(</div>
<div class="line"><a id="l00173" name="l00173"></a><span class="lineno">  173</span>        <a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#af923f26f3d015156bb5ac159b302311b" title="Const references to BatchInputType.">ConstBatchInputReference</a> batchX1, </div>
<div class="line"><a id="l00174" name="l00174"></a><span class="lineno">  174</span>        <a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#af923f26f3d015156bb5ac159b302311b" title="Const references to BatchInputType.">ConstBatchInputReference</a> batchX2, </div>
<div class="line"><a id="l00175" name="l00175"></a><span class="lineno">  175</span>        RealMatrix <span class="keyword">const</span>&amp; coefficients,</div>
<div class="line"><a id="l00176" name="l00176"></a><span class="lineno">  176</span>        <a class="code hl_struct" href="structshark_1_1_state.html" title="Represents the State of an Object.">State</a> <span class="keyword">const</span>&amp; state, </div>
<div class="line"><a id="l00177" name="l00177"></a><span class="lineno">  177</span>        RealVector&amp; gradient</div>
<div class="line"><a id="l00178" name="l00178"></a><span class="lineno">  178</span>    )<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00179" name="l00179"></a><span class="lineno">  179</span>        <a class="code hl_define" href="_flags_8h.html#a6e41326253dee198183b5cbde3570c6c">SHARK_FEATURE_EXCEPTION</a>(<a class="code hl_enumvalue" href="classshark_1_1_abstract_kernel_function.html#af54c80ca837961761506e6c2eec15bdead621a9ae065d91a154055a38a7ea72f8" title="is the kernel differentiable w.r.t. its parameters?">HAS_FIRST_PARAMETER_DERIVATIVE</a>);</div>
<div class="line"><a id="l00180" name="l00180"></a><span class="lineno">  180</span>    }</div>
</div>
<div class="line"><a id="l00181" name="l00181"></a><span class="lineno">  181</span><span class="comment"></span> </div>
<div class="line"><a id="l00182" name="l00182"></a><span class="lineno">  182</span><span class="comment">    /// \brief Calculates the derivative of the inputs X1 (only x1!).</span></div>
<div class="line"><a id="l00183" name="l00183"></a><span class="lineno">  183</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00184" name="l00184"></a><span class="lineno">  184</span><span class="comment">    /// The i-th row of the resulting matrix is a weighted sum of the form:</span></div>
<div class="line"><a id="l00185" name="l00185"></a><span class="lineno">  185</span><span class="comment">    /// c[i,0] * k&#39;(x1[i], x2[0]) + c[i,1] * k&#39;(x1[i], x2[1]) + ... + c[i,n] * k&#39;(x1[i], x2[n]).</span></div>
<div class="line"><a id="l00186" name="l00186"></a><span class="lineno">  186</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00187" name="l00187"></a><span class="lineno">  187</span><span class="comment">    /// The default implementation throws a &quot;not implemented&quot; exception.</span></div>
<div class="foldopen" id="foldopen00188" data-start="{" data-end="}">
<div class="line"><a id="l00188" name="l00188"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#af534a7a45f73baab879c2f0bfb75f00a">  188</a></span><span class="comment"></span>    <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#af534a7a45f73baab879c2f0bfb75f00a" title="Calculates the derivative of the inputs X1 (only x1!).">weightedInputDerivative</a>( </div>
<div class="line"><a id="l00189" name="l00189"></a><span class="lineno">  189</span>        <a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#af923f26f3d015156bb5ac159b302311b" title="Const references to BatchInputType.">ConstBatchInputReference</a> batchX1, </div>
<div class="line"><a id="l00190" name="l00190"></a><span class="lineno">  190</span>        <a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#af923f26f3d015156bb5ac159b302311b" title="Const references to BatchInputType.">ConstBatchInputReference</a> batchX2, </div>
<div class="line"><a id="l00191" name="l00191"></a><span class="lineno">  191</span>        RealMatrix <span class="keyword">const</span>&amp; coefficientsX2,</div>
<div class="line"><a id="l00192" name="l00192"></a><span class="lineno">  192</span>        <a class="code hl_struct" href="structshark_1_1_state.html" title="Represents the State of an Object.">State</a> <span class="keyword">const</span>&amp; state, </div>
<div class="line"><a id="l00193" name="l00193"></a><span class="lineno">  193</span>        <a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#adbf700c2ece7236c70cef4b88777a733" title="batch input type of the kernel">BatchInputType</a>&amp; gradient</div>
<div class="line"><a id="l00194" name="l00194"></a><span class="lineno">  194</span>    )<span class="keyword"> const </span>{</div>
<div class="line"><a id="l00195" name="l00195"></a><span class="lineno">  195</span>        <a class="code hl_define" href="_flags_8h.html#a6e41326253dee198183b5cbde3570c6c">SHARK_FEATURE_EXCEPTION</a>(<a class="code hl_enumvalue" href="classshark_1_1_abstract_kernel_function.html#af54c80ca837961761506e6c2eec15bdeae4bd575af084f862f64bc665cad4c4ec" title="is the kernel differentiable w.r.t. its inputs?">HAS_FIRST_INPUT_DERIVATIVE</a>);</div>
<div class="line"><a id="l00196" name="l00196"></a><span class="lineno">  196</span>    }</div>
</div>
<div class="line"><a id="l00197" name="l00197"></a><span class="lineno">  197</span> </div>
<div class="line"><a id="l00198" name="l00198"></a><span class="lineno">  198</span><span class="comment"></span> </div>
<div class="line"><a id="l00199" name="l00199"></a><span class="lineno">  199</span><span class="comment">    //////////////////////////////////NORMS AND DISTANCES/////////////////////////////////</span></div>
<div class="line"><a id="l00200" name="l00200"></a><span class="lineno">  200</span><span class="comment"></span><span class="comment"></span> </div>
<div class="line"><a id="l00201" name="l00201"></a><span class="lineno">  201</span><span class="comment">    /// Computes the squared distance in the kernel induced feature space.</span></div>
<div class="foldopen" id="foldopen00202" data-start="{" data-end="}">
<div class="line"><a id="l00202" name="l00202"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#a4526b02196952d7af3bc76633c8bd6b7">  202</a></span><span class="comment"></span>    <span class="keyword">virtual</span> <span class="keywordtype">double</span> <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#a4526b02196952d7af3bc76633c8bd6b7" title="Computes the squared distance in the kernel induced feature space.">featureDistanceSqr</a>(<a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#a40e365cb5ec7d2776105a4aef4e78df3" title="Const references to InputType.">ConstInputReference</a> x1, <a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#a40e365cb5ec7d2776105a4aef4e78df3" title="Const references to InputType.">ConstInputReference</a> x2)<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00203" name="l00203"></a><span class="lineno">  203</span>        <span class="keywordflow">if</span> (<a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#a3b60def6354aac30a9c2ce5bffa6f9ae">isNormalized</a>()){</div>
<div class="line"><a id="l00204" name="l00204"></a><span class="lineno">  204</span>            <span class="keywordtype">double</span> k12 = <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#abd10e3815efade90c7f9e2a7cc8bcb6c" title="Evaluates the kernel function.">eval</a>(x1, x2);</div>
<div class="line"><a id="l00205" name="l00205"></a><span class="lineno">  205</span>            <span class="keywordflow">return</span> (2.0 - 2.0 * k12);</div>
<div class="line"><a id="l00206" name="l00206"></a><span class="lineno">  206</span>        } <span class="keywordflow">else</span> {</div>
<div class="line"><a id="l00207" name="l00207"></a><span class="lineno">  207</span>            <span class="keywordtype">double</span> k11 = <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#abd10e3815efade90c7f9e2a7cc8bcb6c" title="Evaluates the kernel function.">eval</a>(x1, x1);</div>
<div class="line"><a id="l00208" name="l00208"></a><span class="lineno">  208</span>            <span class="keywordtype">double</span> k12 = <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#abd10e3815efade90c7f9e2a7cc8bcb6c" title="Evaluates the kernel function.">eval</a>(x1, x2);</div>
<div class="line"><a id="l00209" name="l00209"></a><span class="lineno">  209</span>            <span class="keywordtype">double</span> k22 = <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#abd10e3815efade90c7f9e2a7cc8bcb6c" title="Evaluates the kernel function.">eval</a>(x2, x2);</div>
<div class="line"><a id="l00210" name="l00210"></a><span class="lineno">  210</span>            <span class="keywordflow">return</span> (k11 - 2.0 * k12 + k22);</div>
<div class="line"><a id="l00211" name="l00211"></a><span class="lineno">  211</span>        }</div>
<div class="line"><a id="l00212" name="l00212"></a><span class="lineno">  212</span>    }</div>
</div>
<div class="line"><a id="l00213" name="l00213"></a><span class="lineno">  213</span>    </div>
<div class="foldopen" id="foldopen00214" data-start="{" data-end="}">
<div class="line"><a id="l00214" name="l00214"></a><span class="lineno"><a class="line" href="classshark_1_1_abstract_kernel_function.html#a5abde1fffe84a51cb07c2242eef632ef">  214</a></span>    <span class="keyword">virtual</span> RealMatrix <a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#a5abde1fffe84a51cb07c2242eef632ef" title="Computes the squared distance in the kernel induced feature space.">featureDistanceSqr</a>(<a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#af923f26f3d015156bb5ac159b302311b" title="Const references to BatchInputType.">ConstBatchInputReference</a> batchX1,<a class="code hl_typedef" href="classshark_1_1_abstract_kernel_function.html#af923f26f3d015156bb5ac159b302311b" title="Const references to BatchInputType.">ConstBatchInputReference</a> batchX2)<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00215" name="l00215"></a><span class="lineno">  215</span>        std::size_t sizeX1 = <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>(batchX1);</div>
<div class="line"><a id="l00216" name="l00216"></a><span class="lineno">  216</span>        std::size_t sizeX2 = <a class="code hl_function" href="namespaceshark.html#af2ab10364feb8a631e0866dcf2f1a4ad">batchSize</a>(batchX2);</div>
<div class="line"><a id="l00217" name="l00217"></a><span class="lineno">  217</span>        RealMatrix result=(*this)(batchX1,batchX2);</div>
<div class="line"><a id="l00218" name="l00218"></a><span class="lineno">  218</span>        result *= -2.0;</div>
<div class="line"><a id="l00219" name="l00219"></a><span class="lineno">  219</span>        <span class="keywordflow">if</span> (<a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#a3b60def6354aac30a9c2ce5bffa6f9ae">isNormalized</a>()){</div>
<div class="line"><a id="l00220" name="l00220"></a><span class="lineno">  220</span>            noalias(result) += 2.0;</div>
<div class="line"><a id="l00221" name="l00221"></a><span class="lineno">  221</span>        } <span class="keywordflow">else</span> {</div>
<div class="line"><a id="l00222" name="l00222"></a><span class="lineno">  222</span>            <span class="comment">//compute self-product</span></div>
<div class="line"><a id="l00223" name="l00223"></a><span class="lineno">  223</span>            RealVector kx2(sizeX2);</div>
<div class="line"><a id="l00224" name="l00224"></a><span class="lineno">  224</span>            <span class="keywordflow">for</span>(std::size_t i = 0; i != sizeX2;++i){</div>
<div class="line"><a id="l00225" name="l00225"></a><span class="lineno">  225</span>                kx2(i)=<a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#abd10e3815efade90c7f9e2a7cc8bcb6c" title="Evaluates the kernel function.">eval</a>(<a class="code hl_function" href="namespaceshark.html#a1531880b9b4076854b0b26441d353242">getBatchElement</a>(batchX2,i),<a class="code hl_function" href="namespaceshark.html#a1531880b9b4076854b0b26441d353242">getBatchElement</a>(batchX2,i));</div>
<div class="line"><a id="l00226" name="l00226"></a><span class="lineno">  226</span>            }</div>
<div class="line"><a id="l00227" name="l00227"></a><span class="lineno">  227</span>            <span class="keywordflow">for</span>(std::size_t j = 0; j != sizeX1;++j){</div>
<div class="line"><a id="l00228" name="l00228"></a><span class="lineno">  228</span>                <span class="keywordtype">double</span> kx1=<a class="code hl_function" href="classshark_1_1_abstract_kernel_function.html#abd10e3815efade90c7f9e2a7cc8bcb6c" title="Evaluates the kernel function.">eval</a>(<a class="code hl_function" href="namespaceshark.html#a1531880b9b4076854b0b26441d353242">getBatchElement</a>(batchX1,j),<a class="code hl_function" href="namespaceshark.html#a1531880b9b4076854b0b26441d353242">getBatchElement</a>(batchX1,j));</div>
<div class="line"><a id="l00229" name="l00229"></a><span class="lineno">  229</span>                noalias(row(result,j)) += kx1 + kx2;</div>
<div class="line"><a id="l00230" name="l00230"></a><span class="lineno">  230</span>            }</div>
<div class="line"><a id="l00231" name="l00231"></a><span class="lineno">  231</span>        }</div>
<div class="line"><a id="l00232" name="l00232"></a><span class="lineno">  232</span>        <span class="keywordflow">return</span> result;</div>
<div class="line"><a id="l00233" name="l00233"></a><span class="lineno">  233</span>    }</div>
</div>
<div class="line"><a id="l00234" name="l00234"></a><span class="lineno">  234</span>};</div>
</div>
<div class="line"><a id="l00235" name="l00235"></a><span class="lineno">  235</span> </div>
<div class="line"><a id="l00236" name="l00236"></a><span class="lineno">  236</span> </div>
<div class="line"><a id="l00237" name="l00237"></a><span class="lineno">  237</span>}</div>
<div class="line"><a id="l00238" name="l00238"></a><span class="lineno">  238</span><span class="preprocessor">#endif</span></div>
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